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Proceedings Paper

Transform image coding using broad vector quantization
Author(s): Ahmad C. Ansari; Mazin Rahim
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Paper Abstract

An adaptive discrete cosine transform (DCT) method for image compression is presented. Clustering technique based on vector quantization (VQ) is used to reconstruct binary patterns representing the location maps of selected DCT coefficients. The DCT of image blocks are classified into broad categories and after quantization, the transform coefficients are encoded using a variable word length (VWL) coding scheme. It is demonstrated that this approach is well-suited for real-time visual communications systems, and performs efficiently at very low bit rates.

Paper Details

Date Published: 1 July 1992
PDF: 6 pages
Proc. SPIE 1702, Hybrid Image and Signal Processing III, (1 July 1992); doi: 10.1117/12.60567
Show Author Affiliations
Ahmad C. Ansari, Rutgers Univ. (United States)
Mazin Rahim, Rutgers Univ. (United States)

Published in SPIE Proceedings Vol. 1702:
Hybrid Image and Signal Processing III
David P. Casasent; Andrew G. Tescher, Editor(s)

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